Table REF  shows the performance of POMP against the baselines with a detector provided by the same authors of the AVDB [1]}. The detector is similar to Faster-RCNN[2]} but with additional input as the reference images of the target object, in order to improve the detection quality.
We use the pre-trained model without any customisation. The detector achieves a precision of 0.73 and a recall of 0.53 under the confidence threshold of 0.9. On average, our method with path replanning improves the SR with a slight increase in APL, which is consistent with what we observe in Fig. REF .
In terms of processing speed, we run experiments on a machine with 6-core Intel i7-6800k CPU, achieving 0.07 seconds per step on average.
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